Conventional Multiple Input Multiple Output or MIMO wireless systems exploit the use of multiple antennas to improve the wireless transmission performance such as boosting capacity, spectrum efficiency, throughput, range, or other key performance indicators. Typically, conventional MIMO systems use a small number of antennas such as less than 10. If the number of antennas is large, such as 32 or more, the MIMO system is usually called Massive MIMO. The antennas of typical Massive MIMO systems are placed in planar arrays of various sizes such as 4×8, 8×8, 4×12, etc. The actual size of an array is called the aperture of the antenna system.
Multiple antennas have the capability of producing transmit/receive diversity, i.e. producing transmit/receive antenna signals, which are mutually independent. This diversity is the necessary and essential ingredient of MIMO systems. It is important to emphasize that in general not all ensembles of multiple antennas chosen arbitrarily provide diversity. A multiple antenna system must be constructed in special ways to provide diversity. Antenna systems providing partial diversity, i.e. providing signals that are only partially independent, are also possible. The number of antennas and the number of independent antenna signals obtained, known as “order of diversity,” are not necessarily the same. The order of diversity cannot be larger than the number of antennas, but the number of antennas can be much larger than the order of diversity obtained. In general, for MIMO systems, the larger the order of diversity the better and the more potential benefits to the wireless communication system. The order of diversity is sometimes also referred to as “degrees of freedom” for the wireless communication system.
Multiple antennas usually provide two types of diversity: polarization diversity and spatial diversity. The polarization diversity is typically achieved by using two identical antennas, which are physically rotated by 90 degrees from each other around the axis pointing on the direction of maximum transmitted or received RF energy. In practice, only two antennas with orthogonal polarizations can be realized, i.e., polarizations producing independent antenna signals (100% diversity), because any rotation other than 90 degrees generates coupling between the two antennas. Therefore, a MIMO system using only polarization diversity cannot have diversity of order larger than two. The original 4G LTE cellular system was deployed with two antennas providing only polarization diversity.
Spatial diversity may be obtained by placing antennas far enough from each other, a necessary but not sufficient condition. In practice, achieving good spatial diversity with multiple antennas is more problematic than achieving polarization diversity because spatial diversity is not only a function of the antenna system construction and physical placing but also of the scattering environment in which the antennas transmit/receive signals. For example, in an environment without any scattering (e.g., free space), there is no spatial diversity no matter how many antennas are used, how far they are placed from each other, or how they are constructed. This is because all signals transmitted/received in an environment without scattering are 100% correlated.
The main object of MIMO is to capitalize on the diversity of the system to transmit and receive in parallel multiple independent signals over the same frequency bands. This spectrum reuse operation is known as spatial multiplexing and it is the most important method for increasing the capacity of the wireless communication systems. The parallel independent signals transmitted are also called “layers”. The 2×2 MIMO (two antennas at the transmitting node and two antennas at the receiving node) with polarization diversity at each node, originally deployed in 4G LTE, supports two layers doubling the maximum data rate of the similar single antenna system also known as Single Input Single Output of SISO (single antenna at the transmitting node and a single antenna at the receiving node). This is because the 2×2 MIMO system has the order of diversity two while SISO has the order of diversity one. A 4×4 MIMO (four antennas at the transmitting node and four antennas at the receiving node) has the theoretical potential of quadrupling the maximum data rate of a similar SISO system. However, in practice the data rate increase in most situations is less than four times that of SISO because the order of diversity of the system is less than four, despite the use of four antennas. As explained earlier, the culprit is the lack of sufficient spatial diversity due to either two little antenna separation or lack of enough scattering or both. As the number of antennas is increased, the practical gains in the system order of diversity get smaller and smaller. It is not uncommon for a Massive MIMO system with 64 antennas or more to have an order of diversity less than ten.
Regarding the design of MIMO systems, an important practical matter is finding the optimum system architecture that fully exploits the order of diversity of the system while minimizing the system complexity. In the case of regular MIMO (e.g. 10 or fewer antennas) the “one full radio per antenna” architecture also known as “Digital” MIMO is the appropriate architecture. While not always strictly optimum (e.g. for 8×8 MIMO the average number of layers is less than 8), this architecture is still reasonable in complexity with only 2-8 radios and provides a system supporting many layers. The case of Massive MIMO systems is different and is discussed next.
A popular Massive-MIMO architecture called Digital Massive MIMO is based on the brute-force scaling of the “one full radio per antenna” architecture of regular MIMO. Therefore, for 32 antennas there are 32 radios with 32 analog-to-digital converters (ADCs) and 32 digital-to-analog converters (DACs), for 64 antennas there are 64 radios with 64 ADCs and 64 DACs, and so on. This architecture is straightforward and quite flexible in terms of digital signal processing possibilities because the MIMO digital processor is connected directly to every antenna element. Traditionally this has been viewed as a major benefit because all MIMO processing such as spatial multiplexing (explained earlier), beamforming (focusing the RF energy towards some users), nulling (removing the RF energy towards other users), etc. are done in the digital domain under software control. More specifically, all phase and magnitude settings of the antenna signals, which determine the radiation patterns of the system are done in software. The analog radios are just “dumb pipes” carrying the signals between the MIMO digital processor and the antennas. In addition, this architecture allows for the processing of orthogonal pilot signals for each antenna, i.e., pilot signals that are mutually independent and can be detected separately. These pilot signals are useful for estimating the channel characteristics between the communication points and are employed commonly in standard communication protocols. Yet another benefit of the Digital MIMO is that independent MIMO processing can be done per frequency sub-bands. For example, in 4G LTE, during a time interval called “sub-frame”, multiple users occupying different frequency sub-bands can be processed independently, allowing beamforming in different directions for each respective user. This is called “per-user beamforming”.
As mentioned earlier, in most practical cases and for fundamental reasons, the number of layers supported by any Massive MIMO system including the Digital Massive MIMO is far less than the number of antennas used. Since the digital Massive MIMO has as many full radios as there are antennas, there is an inherent and severe inefficiency in these systems in terms of necessary hardware resources, cost, and power dissipation. This will become apparent after the embodiments are described below.
While previously we mentioned only the large number of data converters necessary in Digital Massive MIMO systems, which are expensive and power-hungry components, other such components (expensive and power-hungry) are also necessary. These include high precision analog channel filters (one per each transmitter and one per each receiver), high quality RF frequency synthesizers (one per radio) and high-speed low-jitter digital circuits (custom ICs or FPGAs) for digital signal transport, splitting and aggregation. These components have not been subject to the usual dramatic cost/power Moore's Law improvements, typically experienced in the past for regular digital integrated circuits. Furthermore, Moore's Law itself has already reached the end of its life even for regular digital integrated circuits.
The radios in the Massive MIMO system use many other components, which in terms of cost and power dissipation have benefited in the past from both Moor's Law and from huge production volumes in consumer electronics including mobile phones. These components implement classical transceiver functions such as mixers, intermediate frequency (IF) variable-gain amplifiers (VGAs), RF amplifiers and support biasing and power circuits. Typically, these components are integrated into low-cost, low-power ICs. This is an important capability, which is exploited by embodiments described herein.
Another possible Massive-MIMO architecture is Hybrid Massive MIMO. In this architecture, the number of ADCs and DACs and the other high-cost, high-power components mentioned before is far less than the number of antennas. Since there are not enough digital paths to control the phases and magnitudes of all antenna elements by software, the Hybrid Massive MIMO system adds analog phase shifters and gain blocks for amplitude control behind each antenna element. These additional components are usually controlled by digital means and are in the category of low-cost, low-power components mentioned earlier.
In a Hybrid Massive MIMO system, the radiation patterns are produced partially in the digital domain through phase/magnitude setting of the digital signals flowing through the data converters and partially in the analog domain through the phase/magnitude settings of the analog phase shifters and gain blocks, hence the name “hybrid”.
By construction, the Hybrid Massive MIMO system is significantly more efficient than the Digital Massive MIMO system in terms of hardware, cost and power dissipation. However, the Hybrid Massive MIMO system has been regarded as inferior to Digital Massive MIMO due to limited number of digital connections to the MIMO digital processor. Furthermore, the ability of Hybrid Massive-MIMO to provide independent pilots for each antenna element and perform per-user beamforming have also been put in doubt.